Structural metadata is the most misunderstood form of metadata. It is widely ignored, even among those who work with metadata. When it is discussed, it gets confused with other things. Even people who understand structural metadata correctly don’t always appreciate its full potential. That’s unfortunate, because structural metadata can make content more powerful. This post takes a deep dive into what structural metadata is, what it does, and how it is changing.
Why should you care about structural metadata? The immediate, self-interested answer is that structural metadata facilitates content reuse, taking content that’s already created to deliver new content. Content reuse is nice for publishers, but it isn’t a big deal for audiences. Audiences don’t care how hard it is for the publisher to create their content. Audiences want content that matches their needs precisely, and that’s easy to use. Structural metadata can help with that too.
Structural metadata matches content with the needs of audiences. Content delivery can evolve beyond creating many variations of content — the current preoccupation of many publishers. Publishers can use structural metadata to deliver more interactive content experiences. Structural metadata will be pivotal in the development of multimodal content, allowing new forms of interaction, such as voice interaction. Well-described chunks of content are like well-described buttons, sliders and other forms of interactive web elements. The only difference is that they are more interesting. They have something to say.
Some of the following material will assume background knowledge about metadata. If you need more context, consult my very approachable book, Metadata Basics for Web Content.
What is Structural Metadata?
Structural metadata is data about the structure of content. In some ways it is not mysterious at all. Every time you write a paragraph, and enclose it within a
<p> paragraph element, you’ve created some structural metadata. But structural metadata entails far more than basic HTML tagging. It gives data to machines on how to deliver the content to audiences. When structural metadata is considered as a fancy name for HTML tagging, much of its potency gets missed.
The concept of structural metadata originated in the library and records management field around 20 years ago. To understand where structural metadata is heading, it pays to look at how it has been defined already.
In 1996, a metadata initiative known as the Warwick Framework first identified structural metadata as “data defining the logical components of complex or compound objects and how to access those components.”
In 2001, a group of archivists, who need to keep track of the relationships between different items of content, came up with a succinct definition: “Structural metadata can be thought of as the glue that binds compound objects together.”
By 2004, the National Information Standards Organization (NISO) was talking about structural metadata in their standards. According to their definition in the z39.18 standard, “Structural metadata explain the relationship between parts of multipart objects and enhance internal navigation. Such metadata include a table of contents or list of figures and tables.”
Louis Rosenfeld and Peter Morville introduced the concept of structural metadata to the web community in their popular book, Information Architecture for the World Wide Web — the “Polar Bear” book. Rosenfeld and Morville use the structural metadata concept as a prompt to define the information architecture of a websites:
“Describe the information hierarchy of this object. Is there a title? Are there discrete sections or chunks of content? Might users want to independently access these chunks?”
A big theme of all these definitions is the value of breaking content into parts. The bigger the content, the more it needs breaking down. The structural metadata for a book relates to its components: the table of contents, the chapters, parts, index and so on. It helps us understand what kinds of material is within the book, to access specific sections of the book, even if it doesn’t tell us all the specific things the book discusses. This is important information, which surprisingly, wasn’t captured when Google undertook their massive book digitization initiative a number of years ago. When the books were scanned, entire books became one big file, like a PDF. To find a specific figure or table within book on Google books requires searching or scrolling to navigate through the book.
Navigation is an important purpose of structural metadata: to access specific content, such as a specific book chapter. But structural metadata has an even more important purpose than making big content more manageable. It can unbundle the content, so that the content doesn’t need to stay together. People don’t want to start with the whole book and then navigate through it to get to a small part in which they are interested. They want only that part.
In his recent book Metadata, Richard Gartner touches on a more current role for structural metadata: “it defines structures that bring together simpler components into something larger that has meaning to a user.” He adds that such information “builds links between small pieces of data to assemble them into a more complex object.”
In web content, structural metadata plays an important role assembling content. When content is unbundled, it can be rebundled in various ways. Structural metadata identifies the components within content types. It indicates role of the content, such as whether the content is an introduction or a summary.
Structural metadata plays a different role today than it did in the past, when the assumption was that there was one fixed piece of large content that would be broken into smaller parts, identified by structural metadata. Today, we may compose many larger content items, leveraging structural metadata, from smaller parts.
The idea of assembling content from smaller parts has been promoted in particular by DITA evangelists such as Anne Rockley (DITA is a widely used framework for technical documentation). Rockley uses the phrase “semantic structures” to refer to structural metadata, which she says “enable(s) us to understand ‘what’ types of content are contained within the documents and other content types we create.” Rockley’s discussion helpfully makes reference to content types, which some other definitions don’t explicitly mention. She also introduces another concept with a similar sounding name, “semantically rich” content, to refer to a different kind of metadata: descriptive metadata. In XML (which is used to represent DITA), the term semantic is used generically for any element. Yet the difference between structural and descriptive metadata is significant — though it is often obscured, especially in the XML syntax.
Curiously, semantic web developments haven’t focused much on structural metadata for content (though I see a few indications that this is starting to change). Never assume that when someone talks about making content semantic, they are talking about adding structural metadata.
Don’t Confuse Structural and Descriptive Metadata
When information professionals refer to metadata, most often they are talking about descriptive metadata concerning people, places, things, and events. Descriptive metadata indicates the key information included within the content. It typically describes the subject matter of the content, and is sometimes detailed and extensive. It helps one discover what the content is about, prior to viewing the content. Traditionally, descriptive metadata was about creating an external index — a proxy — such as assigning a keywords or subject headings about the content. Over the past 20 years, descriptive metadata has evolved to describing the body of the content in detail, noting entities and their properties.
Richard Gartner refers to descriptive metadata as “finding metadata”: it locates content that contains some specific information. In modern web technology, it means finding values for a specific field (or property). These values are part of the content, rather than separate from it. For example, find smartphones with dual SIMs that are under $400. The attributes of SIM capacity and price are descriptive metadata related to the content describing the smartphones.
Structural metadata indicates how people and machines can use the content. If people see a link indicating a slideshow, they have an expectation of how such content will behave, and will decide if that’s the sort of content they are interested in. If a machine sees that the content is a table, it uses that knowledge to format the content appropriately on a smartphone, so that all the columns are visible. Machines rely extensively on structural metadata when stitching together different content components into a larger content item.
Structural metadata sometimes is confused with descriptive metadata because many people use vague terms such as “structure” and “semantics” when discussing content. Some people erroneously believe that structuring content makes the content “semantic”. Part of this confusion derives from having an XML-orientation toward content. XML tags content with angle-bracketed elements. But XML elements can be either structures such as sections, or they can be descriptions such as names. Unlike HTML, where elements signify content structure while descriptions are indicated in attributes, the XML syntax creates a monster hierarchical tree, where content with all kinds of roles are nested within elements. The motley, unpredictable use of elements in XML is a major reason it is unpopular with developers, who have trouble seeing what roles different parts of the content have.
The buzzword “semantically structured content” is particularly unhelpful, as it conflates two different ideas together: semantics, or what content means, with structure, or how content fits together. The semantics of the content is indicated by descriptive metadata, while the structure of the content is indicated by structural metadata. Descriptive metadata can focus on a small detail in the content, such as a name or concept (e.g., here’s a mention of the Federal Reserve Board chair in this article). Structural metadata, in contrast, generally focuses on a bigger chunk of content: here’s a table, here’s a sidebar. To assemble content, machines need to distinguish what the specific content means, from what the structure of the content means.
Interest in content modeling has grown recently, spurred by the desire to reuse content in different contexts. Unfortunately, most content models I’ve seen don’t address metadata at all; they just assume that the content can be pieced together. The models almost never distinguish between the properties of different entities (descriptive metadata), and the properties of different content types (structural metadata). This can lead to confusion. For example, a place has an address, and that address can be used in many kinds of content. You may have specific content types dedicated to discussing places (perhaps tourist destinations) and want to include address information. Alternatively, you may need to include the address information in content types that are focused on other purposes, such as a membership list. Unless you make a clear distinction in the content model between what’s descriptive metadata about entities, and what’s structural metadata about content types, many people will be inclined to think there is a one-to-one correspondence between entities and content types, for example, all addresses belong the the content type discussing tourist destinations.
Structural metadata isn’t merely a technical issue to hand off to a developer. Everyone on a content team who is involved with defining what content gets delivered to audiences, needs to jointly define what structural metadata to include in the content.
Three More Reasons Structural Metadata Gets Ignored…
Content strategists have inherited frameworks for working with metadata from librarians, database experts and developers. None of those roles involves creating content, and their perspective of content is an external one, rather than an internal one. These hand-me-down concepts don’t fit the needs of online content creators and publishers very well. It’s important not to be misled by legacy ideas about structural metadata that were developed by people who aren’t content creators and publishers. Structural metadata gets sidelined when people fail to focus on the value that content parts can contribute in different scenarios.
Reason 1: Focus on Whole Object Metadata
Librarians have given little attention to structural metadata, because they’ve been most concerned with cataloging and locating things that have well defined boundaries, such as books and articles (and most recently, webpages). Discussion of structural metadata in library science literature is sparse compared with discussions of descriptive and administrative metadata.
Until recently, structural metadata has focused on identifying parts within a whole. Metadata specialists assumed that a complete content item existed (a book or document), and that structural metadata would be used to locate parts within the content. Specifying structural metadata was part of cataloging existing materials. But given the availability of free text searching and more recently natural language processing, many developers question the necessity of adding metadata to sub-divide a document. Coding structural metadata seemed like a luxury, and got ignored.
In today’s web, content exists as fragments that can be assembled in various ways. A document or other content type is a virtual construct, awaiting components. The structural metadata forms part of the plan for how the content can fit together. It’s important to define the pieces first.
Reason 2: Confusion with Metadata Schemas
I’ve recently seen several cases where content strategists and others mix up the concept of structural metadata, with the concept of metadata structure, better known as metadata schemas. At first I thought this confusion was simply the result of similar sounding terms. But I’ve come to realize that some database experts refer to structural metadata in a different way than it is being used by librarians, information architects, and content engineers. Some content strategists seem to have picked up this alternative meaning, and repeat it.
Compared to semi-structured web content, databases are highly regular in structure. They are composed of tables of rows and columns. The first column of a row typically identifies what the values relate to. Some database admins refer to those keys or properties as the structure of the data, or the structural metadata. For example, the OECD, the international statistical organization, says: “Structural metadata refers to metadata that act as identifiers and descriptors of the data. Structural metadata are needed to identify, use, and process data matrixes and data cubes.” What is actually being referred to is the schema of the data table.
Database architects develop many custom schemas to organize their data in tables. Those schemas are very different from the standards-based structural metadata used in content. Database tables provide little guidance on how content should be structured. Content teams shouldn’t rely on a database expert to guide them on how to structure their content.
Reason 3: Treated as Ordinary Code
Web content management systems are essentially big databases built in programming language like PHP or .Net. There’s a proclivity among developers to treat chunks of content as custom variables. As one developer noted when discussing WordPress: “In WordPress (WP), the meaning of Metadata is a bit fuzzier. It stores post metadata such as custom fields and additional metadata added via plugins.”
As I’ve noted elsewhere, many IT systems that manage content ignore web metadata standards, resulting in silos of content that can’t work together. It’s not acceptable to define chunks of content as custom variables. The purpose of structural metadata is to allow different chunks of content to connect with each other. CMSs need to rely on web standards for their structural metadata.
Current Practices for Structural Metadata
For machines to piece together content components into a coherent whole, they need to know the standards for the structural metadata.
Until recently, structural metadata has been indicated only during the prepublication phase, an internal operation where standards were less important. Structural metadata was marked up in XML together with other kinds of metadata, and transformed into HTML or PDF. Yet a study in the journal Semantic Web last year noted: “Unfortunately, the number of distinct vocabularies adopted by publishers to describe these requirements is quite large, expressed in bespoke document type definitions (DTDs). There is thus a need to integrate these different languages into a single, unifying framework that may be used for all content.”
XML continues to be used in many situations. But a recent trend has been to adopt more light weight approaches, using HTML, to publish content directly. Bypassing XML is often simpler, though the plainness of HTML creates some issues as well.
As Jeff Eaton has noted, getting specific about the structure of content using HTML elements is not always easy:
“We have workhorse elements like ul, div, and span; precision tools like cite, table, and figure; and new HTML5 container elements like section, aside, and nav. But unless our content is really as simple as an unattributed block quote or a floated image, we still need layers of nested elements and CSS classes to capture what we really mean.”
Because HTML elements are not very specific, publishers often don’t know how to represent structural metadata within HTML. We can learn from the experience of publishers who have used XML to indicate structure, and who are adapting their structures to HTML.
Scientific research, and technical documentation are two genres where content structure is well-established, and structural metadata is mature. Both these genres have explored how to indicate the structure of their content in HTML.
Scientific research papers are a distinct content type that follows a regular pattern. The National Library of Medicine’s Journal Article Tag Suite (JATS) formalizes the research paper structure into a content type as an XML schema. It provides a mixture of structural and descriptive metadata tags that are used to publish biomedical and other scientific research. The structure might look like:
<sec sec-type="intro"> <sec sec-type="materials|methods"> <sec sec-type="results"> <sec sec-type="discussion"> <sec sec-type="conclusions"> <sec sec-type="supplementary-material" ... >
Scholarly HTML is an initiative to translate the typical sections of a research paper into common HTML. It uses HTML elements, and supplements them with
typeof attributes to indicate more specifically the role of each section. Here’s an example of some attribute values in their namespace, noted by the prefix “sa”:
<section typeof="sa:MaterialsAndMethods"> <section typeof="sa:Results"> <section typeof="sa:Conclusion"> <section typeof="sa:Acknowledgements"> <section typeof="sa:ReferenceList">
As we can see, these sections overlap with the JATS, since both are describing similar content structures. The Scholarly HTML initiative is still under development, and it could eventually become a part of the schema.org effort.
DITA — the technical documentation architecture mentioned earlier — is a structural metadata framework that embeds some descriptive metadata. DITA structures topics, which can be different information types: Task, Concept, Reference, Glossary Entry, or Troubleshooting, for example. Each type is broken into structural elements, such as title, short description, prolog, body, and related links. DITA is defined in XML, and uses many idiosyncratic tags.
HDITA is a draft syntax to express DITA in HTML. It converts DITA-specific elements into HTML attributes, using the custom
data-* attribute. For example a “key definition” element
<keydef> becomes an attribute within an HTML element, e.g.
. Types are expressed with the attribute
The use of the
“These attributes are not intended for use by software that is not known to the administrators of the site that uses the attributes. For generic extensions that are to be used by multiple independent tools, either this specification should be extended to provide the feature explicitly, or a technology like microdata should be used (with a standardized vocabulary).”
The HDITA drafting committee appears to use “hd” in the data attribute to signify that the attribute is specific to HDITA. But they have not declared a namespace for these attributes (the XML namespace for DITA is
xmlns:ditaarch.) This will prevent automatic machine discovery of the metadata by Google or other parties.
The Future of Structural Metadata
Most recently, several initiatives have explored possibilities for extending structural metadata in HTML. These revolve around three distinct approaches:
- Formalizing structural metadata as properties
- Using WAI-ARIA to indicate structure
- Combining class attributes with other metadata schemas
New Vocabularies for Structures
The web standards community is starting to show more interest in structural metadata. Earlier this year, the W3C released the Web Annotation Vocabulary. It provides properties to indicate comments about content. Comments are an important structure in web content that are used in many genres and scenarios. Imagine that readers may be highlighting passages of text. For such annotations to be captured, there must be a way to indicate what part of the text is being referenced. The annotation vocabulary can reference specific HTML elements and even CSS selectors within a body of text.
Outside of the W3C, a European academic group has developed the Document Components Ontology (DoCO), “a general-purpose structured vocabulary of document elements.” It is a detailed set of properties for describing common structural features of text content. The DoCO vocabulary can be used by anyone, though its initial adoption will likely be limited to research-oriented publishers. However, many specialized vocabularies such as this one have become extensions to schema.org. If DoCO were in some form adsorbed by schema.org, its usage would increase dramatically.
WAI-ARIA is commonly thought of as a means to make functionality accessible. However, it should be considered more broadly as a means to enhance the functionality of web content overall, since it helps web agents understand the intentions of the content. WAI-ARIA can indicate many dynamic content structures, such as alerts, feeds, marquees, and regions.
The new Digital Publishing WAI-ARIA developed out of the ePub standards, which have a richer set of structural metadata than is available in standard HTML5. The goal of the Digital Publishing WAI-ARIA is to “produce structural semantic extensions to accommodate the digital publishing industry”. It has the following structural attributes:
To indicate an the structure of a text box showing an example:
<aside role="doc-example"> <h1>An Example of Structural Metadata in WAI-ARIA</h1> … </aside>
Content expressing a warning might look like this:
<div role="doc-notice" aria-label="Explosion Risk"> <p><em>Danger!</em> Mixing reactive materials may cause an explosion.</p> </div>
Although book-focused, DOC-ARIA roles provide a rich set of structural elements that can be used with many kinds of content. In combination with the core WAI-ARIA, these attributes can describe the structure of web content in extensive detail.
CSS as Structure
For a long while, developers have been creating pseudo structures using CSS, such as making infoboxes to enclose certain information. Class is a global attribute of HTML, but has become closely associated with CSS, so much so that some believe that is its only purpose. Yet Wikipedia notes: “The class attribute provides a way of classifying similar elements. This can be used for semantic purposes, or for presentation purposes.” Some developers use what are called “semantic classes” to indicate what content is about. The W3C advises when using the class attribute: “authors are encouraged to use values that describe the nature of the content, rather than values that describe the desired presentation of the content.”
Some developers claim that the class attribute should never be used to indicate the meaning of content within an element, because HTML elements will always make that clear. I agree that web content should never use the class attribute as a substitute for using a meaningful HTML element. But the class attribute can sometimes further refine the meaning of an HTML element. Its chief limitation is that class names involve private meanings. Yet if they are self-describing they can be useful.
Class attributes are useful for selecting content, but they operate outside of metadata standards. However, schema.org is proposing a property that will allow class values to be specified within schema.org metadata. This has potentially significant implications for extending the scope of structural metadata.
The motivating use case is as follows: “There is a need for authors and publishers to be able to easily call out portions of a Web page that are particularly appropriate for reading out aloud. Such read-aloud functionality may vary from speaking a short title and summary, to speaking a few key sections of a page; in some cases, it may amount to speaking most non-visual content on the page.”
The pending cssSelector property in schema.org can identify named portions of a web page. The class could be a structure such as a summary or a headline that would be more specific than an HTML element. The cssSelector has a companion property called xpath, which identifies HTML elements positionally, such as the paragraphs after h2 headings.
These features are not yet fully defined. In addition to indicating speakable content, the cssSelector can indicate parts of a web page. According to a Github discussion: “The ‘cssSelector’ (and ‘xpath’) property would be particularly useful on http://schema.org/WebPageElement to indicate the part(s) of a page matching the selector / xpath. Note that this isn’t ‘element’ in some formal XML sense, and that the selector might match multiple XML/HTML elements if it is a CSS class selector.” This could be useful selecting content targeted at specific devices.
The class attribute can identify structures within the web content, working together with entity-focused properties that describe specific data relating to the content. Both of these indicate content variables, but they deliver different benefits.
Entity-based (descriptive) metadata can be used for content variables about specific information. They will often serve as text or numeric variables. Use descriptive metadata variables when choosing what informational details to put in a message.
Structural metadata can be used phrase-based variables, indicating reusable components. Phrases can be either blocks (paragraphs or divs), or snippets (a span). Use structural metadata variables when choosing the wording to convey a message in a given scenario.
A final interesting point about cssSelector’s in schema.org. Like other properties in schema.org, these can be expressed either as inline markup in HTML (microdata) or as an external JSON-LD script. This gives developers the flexibility to choose whether to use coding libraries that are optimized for arrays (JSON-flavored), or ones focus on selectors. For too long, what metadata gets included has been influenced by developer preferences in coding libraries. The fact that CSS attributes can be expressed as JSON suggests that hurdle is being transcended.
Structural metadata is finally getting some love in the standards community, even though awareness of it remains low among developers. I hope that content teams will consider how they can use structural metadata to be more precise in indicating what their content does, so that it can be used flexibly in emerging scenarios such as voice interactions.
— Michael Andrews